This has been the third year in a row that I have been doing semi-weekly live streams on R and statistics that I like to call the 'Open Online R Stream': https://www.wvbauer.com/doku.php/live_streams 1/6
#rstats #statistics
Live Streams [Wolfgang Viechtbauer]
2020 I did 87 hours of live streaming, 2021 already 179 hours, and this year 206 hours (that's 8 1/2 full days!). The focus in 2022 was on the book 'An Introduction to Statistical Learning' by James, Witten, Hastie, and Tibshirani (
https://www.statlearning.com), which we have almost finished. 2/6
An Introduction to Statistical Learning
An Introduction to Statistical LearningAside from standard regression type modeling (i.e., linear and logistic regression), the book covered techniques such as the k-nearest neighbor classifier, linear and quadratic discriminant analysis, the naive Bayes classifier, cross-validation and bootstrapping, model selection via subset methods, ridge regression, the Lasso, principal component regression, 3/6
partial least squares, polynomial regression, regression splines, local regression, generalized additive models, tree-based methods such as regression and classification trees, bagging, boosting, random forests, Bayesian additive regression trees, support vector classifiers/machines, single and multilayer neural networks, and convolutional and recurrent neural networks. 4/6
Many methods we implemented 'from scratch' to understand how they really work, but also looked at these packages: alabama, BART, boot, car, class, CVXR, dfoptim, dominanceanalysis, e1071, emmeans, gam, gbm, ggplot2, glmnet, glmulti, ISLR2, jpeg, keras, leaps, MASS, Matrix, mgcv, mvtnorm, nnet, pls, ppcor, pROC, randomForest, relaimpo, rms, scatterplot3d, splines, tree 5/6